Whether you like it or not, your employees are already using AI.
Walk through any modern office and you're likely to see Copilot or ChatGPT hidden behind a spreadsheet, an AI summary drawing key conclusions from a meeting transcript, or an AI-powered scheduling app organizing your calendar.
Pretending otherwise is naive.
It's normal – and, frankly, reasonable – to be at least a little concerned about the use of artificial intelligence. But that doesn't mean you can write it off completely. Artificial intelligence can make your best employees faster and more efficient. It can be a force multiplier for human talent.
Increasingly, this means not only ordinary assistants, but agentic artificial intelligence systems that not only answer questions but also operate autonomously.
The question for management is not whether employees should use AI; what matters is whether they use it safely.
How and why agent-based AI is changing everyday work
Agentic AI is the next evolution of the artificial intelligence tools we all already know.
Instead of simply generating answers or summaries, these systems can scan multiple data sources, decide on the best course of action, and even run workflows without constant human supervision.
In many ways, they are more digital collaborators than mere tools – which is why your best employees use them to increase their efficiency. For example:
- An analyst can reduce hours spent reviewing reports to just a few minutes.
- The sales rep can let the AI agent book appointments and qualify leads while they focus on closing deals.
- A security analyst can relieve the burden of routine log selection, allowing him to devote more time and energy to eliminating real threats.
However, until recently, deploying AI agents required advanced infrastructure, custom pipelines, and continuous child care. To put it simply, agentic artificial intelligence was beyond the reach of almost all organizations.
But that has changed.
Advances like search-assisted generation (RAG), open platforms like LangChain, and cloud-native orchestration have eliminated complexity, making agent-based AI an everyday operational reality.
In fact, if you look closely enough, you can find AI agents in almost every aspect of business.
Where agentic AI is already changing work
AI agents are currently at the peak of inflated expectations in Gartner's AI hype cycle. This means two things: there is a lot of public interest, but there are some unrealistic expectations about what this technology can do and what it can do.
Let's keep it grounded. This is where agentic AI actually makes an impact.
Customer experience
You've probably already had contact with a customer service agent. They can handle routine inquiries around the clock and escalate the most difficult issues to staff.
This means customer-facing teams spend less time on repetitive tasks and more time solving problems that really need to be assessed. Tests Morgan Stanley predicts that retail could save $6 billion thanks to the agent-based efficiency of artificial intelligence.
Sales and Marketing
Coaching agents can analyze CRM data, conduct hands-on role-plays with sales reps, and provide feedback to improve win rates. Others automatically engage incoming prospects, handle objections, and schedule meetings. As a result, salespeople spend less energy on administration and more energy on actually selling.
Healthcare
Agents can review large amounts of clinical data, automate paperwork such as note taking, and even help triage patients in emergency rooms. This means doctors and nurses free up time to care for patients instead of chasing paperwork.
Banking and financial services
Fraud detection agents monitor transactions in real time and stop suspicious activity.
Human Resources
Agents can review resumes, schedule interviews, and help HR teams understand employee feedback. They can also recommend training, monitor compliance, and simplify benefits implementation and management. This allows HR leaders to devote more time to initiatives related to employee care, strategy and retention of high-value employees.
Security operations
SecOps agents can filter alerts, enrich threat intelligence, and suggest response actions. By eliminating noise, they give analysts more time to chase down real intrusions.
The appeal of agent-based AI is obvious. However, the benefits come with tradeoffs, from security and compliance risks to integration challenges, cost overruns, and reliability issues. The same autonomy that makes agentic AI powerful also makes it dangerous without proper protective barriers.
Power has its price…
Agentic AI delivers faster workflows, more accurate insights, and less workload on top people. But these profits don't come for free. Integrating agents with legacy systems can be cumbersome, costs can skyrocket if designs don't deliver a return on investment, and even the most advanced models can still make mistakes or hallucinate.
Moreover, these systems often need access to critical systems and sensitive data, which poses significant security and compliance risks – especially considering that AI agents work autonomously.
These threats may be cumulative. Poor integration undermines reliability, unreliable performance increases costs, and poor management turns efficiency into exposure. And when this happens, the very workers you want to provide AI to are slowing down by fixing or reflecting on its errors.
Moreover, wasted investment is a real possibility. Gartner predicts this is the end By the end of 2027, 40% of agent AI projects will be canceled.
Organizations that move forward without clear pilots and strong guardrails will struggle. Those who implement agent-based AI with discipline (test first, enforce governance, and treat agents as trusted but fallible colleagues) reap the benefits without letting the technology get out of control.
…But standing still is a bigger risk
The risk of using agentic artificial intelligence is enormous.
But the costs NO the use of agent-based artificial intelligence could be even greater.
Relying on legacy systems and manual workflows already carries the risk of inefficiency, burnout, and loss of competitiveness. They are slower, harder to secure, and force employees to waste hours on repetitive tasks.
In the security space in particular, attackers are already using artificial intelligence to scale and accelerate their operations. If defenders stick to manual workflows, they will fight threats at machine speed with tools at human speed.
Investing in and implementing AI is not a choice between safe old tools and risky new ones. It is a choice between managing the risk of modernization and accepting the risk of stagnation. If your employees don't learn to use AI effectively, they fall behind colleagues who do. And if your organization refuses to modernize, you fall behind competitors who already realize the benefits of artificial intelligence.
Your employees know this. That's why they are already experimenting with AI tools on their own. They want to work faster, learn new skills, and avoid wasting time on repetitive, low-value tasks.
Ignoring this reality does not eliminate risk – it simply drives the use of AI underground, where it is more difficult to monitor and control.
What does this mean for your company?
Employees will use artificial intelligence; it is management's responsibility to ensure they do so safely.
Organizations that invest in training and upskilling provide their employees with the knowledge necessary to use artificial intelligence responsibly and effectively. Those that do not leave it to employees to develop ad hoc habits that may be ineffective, uncertain or inconsistent with regulations.
The same applies to retention. Ambitious employees want to be at the forefront and want to work with modern tools. If you block AI, they will either find risky workarounds or go to companies that don't, and these are usually the most effective employees – the ones that AI helps the most.
And finally, performance. Teams that use artificial intelligence with guardrails will deliver more and faster. Teams that cling to outdated workflows will be left behind – not because they lack talent, but because they lack the tools to compete.
